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Automatic Face Annotation System Used Pyramid Database Architecture for Online Social Networks

机译:在线社交网络自动人脸注释系统使用的金字塔数据库体系结构

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摘要

Recently, the development of automatic face annotation techniques in online social networks has become a promising research area for the purpose of management of the large numbers of photographs uploaded to social network platforms. In this paper, we construct the pyramid database for the current owner in the Pyramid Database Access Control module by effectively making use of various types of social network context to drastically reduce time expenditure and further boost the accuracy of face identification for real-life personal photo. In our experiments, our evaluation methodologies produced respective F-measure and Similarity accuracy values that were up to 35.40% and 37.57% higher for the proposed approach in comparison to other face annotation methods. Additionally, our efficiency results demonstrate that the proposed approach can produce a 87.44% reduction in the overall execution time.
机译:近来,出于管理上传到社交网络平台的大量照片的目的,在线社交网络中自动面部注释技术的发展已经成为有前途的研究领域。在本文中,我们通过有效利用各种类型的社交网络上下文在金字塔数据库访问控制模块中为当前所有者构建金字塔数据库,从而大幅减少时间支出并进一步提高真实个人照片中人脸识别的准确性。在我们的实验中,我们的评估方法分别产生了F量度和相似度精度值,与其他人脸标注方法相比,该方法的提议值分别高出35.40%和37.57%。此外,我们的效率结果表明,所提出的方法可以使整体执行时间减少87.44%。

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